Trends and Future of Databases

Future trends

Over time, database expectations have stretched beyond relational models to include non-relational database technology. … General-purpose databases can now support multiple data models, extend capabilities such as spatial and graph, and support data virtualization, distributed storage, and in-memory storage.

There are also some future trends of databases with technology.

Disruptive technologies

Disruptive technologies emerge which create discontinuities that cannot be extrapolated and cannot always be fully anticipated. It’s possible that disruptive new database technology is imminent, but it’s just as likely that the big changes in database technology that have occurred within the last decade represent as much change as we can easily accept. There are a few computing technology trends that extend beyond database architecture and which may impinge heavily on the databases of the future.

Blockchain

Blockchain is the distributed ledger that underlies the Bitcoin cryptocurrency. Blockchain arguably represents a new sort of shared distributed database. Similar to systems based on the Dynamo model, the data in the blockchain is distributed redundantly across a large number of hosts. However, the Blockchain represents a complete paradigm shift in how permissions are managed within the database. In an existing database system, the database owner has absolute control over the data held in the database. However, in a Blockchain system, ownership is maintained by the creator of the data.

Quantum computing

The essential concept is to use subatomic particle behavior as the building blocks of computing.

If quantum computing realizes its theoretical potential it would have an enormous impact on all areas of computing — databases included. There are also some database–specific quantum computing proposals:

AI/ML

It will be interesting to see how artificial intelligence (AI) and machine learning (ML) impact the dynamic elements of data compilation and how it will evolve the database strategy.

Continuing to push the limit of what can be done in real-time versus being computed, Apache stateful processing time goes into coding for streaming engines. ML phenomenon technologies are being inserted into real-time decision making. This is an exciting area for the industry to discover and graphs can enhance ML.

Autonomous

1) The user experience around simplicity. Managed services are taking over and becoming popular easy to get access, management monitoring.

2) High-speed processing opportunities are taking over. We want analytics built-in. Hybrid nature is important.

3) Autonomous databases are becoming the biggest opportunities.

Around autonomous databases: Reduce the operational footprint in terms of security, management, maintainability, and the cost associated with maintaining, making them more automated and autonomous.

Future of databases

distributed databases

A distributed database is a database that consists of two or more files located in different sites either on the same network or on entirely different networks. Portions of the database are stored in multiple physical locations and processing is distributed among multiple database nodes.

Distributed Data Storage

There are 2 ways in which data can be stored on different sites. These are:

1. Replication
In this approach, the entire relation is stored redundantly at 2 or more sites. If the entire database is available at all sites, it is a fully redundant database. Hence, in replication, systems maintain copies of data.
This is advantageous as it increases the availability of data at different sites. Also, now query requests can be processed in parallel.
However, it has certain disadvantages as well. Data needs to be constantly updated. Any change made at one site needs to be recorded at every site that relation is stored or else it may lead to inconsistency. This is a lot of overhead. Also, concurrency control becomes way more complex as concurrent access now needs to be checked over a number of sites.

2. Fragmentation
In this approach, the relations are fragmented and each of the fragments is stored in different sites where they’re required. It must be made sure that the fragments are such that they can be used to reconstruct the original relation
Fragmentation is advantageous as it doesn’t create copies of data, consistency is not a problem.
Fragmentation of relations can be done in two ways:

· Horizontal fragmentation — Splitting by rows — The relation is fragmented into groups of tuples so that each tuple is assigned to at least one fragment.

· Vertical fragmentation — Splitting by columns — The schema of the relation is divided into smaller schemas. Each fragment must contain a common candidate key so as to ensure lossless join.

In certain cases, an approach that is a hybrid of fragmentation and replication is used.

What is the cloud database as a service?

the huge trend of the future of databases is the cloud database concept.

A cloud database is a database service built and accessed through a cloud platform. It serves many of the same functions as a traditional database with the added flexibility of cloud computing. Users install software on a cloud infrastructure to implement the database.

Many companies are deciding to move their data hubs to the cloud. Data volumes are growing, more and more data sources are being made available, and on-premise data centers are becoming a bottleneck. The alternative is to leverage data services on the cloud.

According to market studies, by 2021, DBMS revenue will account for 50% of the total DBMS market revenue. By 2023, 75% of all databases will be on a Cloud platform. These trends will have a major impact on the DBMS vendor landscape.

Gartner published a report that outlines a simple position and thesis: CLOUD IS NOW THE DEFAULT PLATFORM FOR MANAGING DATA. They state:

On-premises is the past, and only legacy compatibility or special requirements should keep you there. Here is the evidence:

1. Gartner numbers show DBMS cloud services are already $10.4 billion of the $46.1 billion DBMS market in 2018. This does not include hosting DBMS licenses in the cloud.
2. Gartner numbers also show that the overall DBMS Market grew at 18.4% from 2017 to 2018 — its best growth in over a decade. Cloud DBMS accounted for 68% of that growth.
3. Only two vendors (Amazon Web Services and Microsoft) account for 75% of the growth from 2017 to 2018. AWS is 100% cloud and Microsoft DBMS growth (we believe) was almost 100% cloud. Cloud growth is dramatically changing vendor rankings (See Figure 1 — and notice the vendors in red boxes)
4. DBMS innovation is cloud-first or cloud-only for development — and often for delivery as well.
5. A majority of the inquiries to Gartner Data Management analysts about DBMS choices are about cloud platforms and migration to these platforms.